The Rheumatologic Diseases Research Informatics Core (Informatics Core) will supply the Pediatric Arthritis clinical genomics research program with computational infrastructure, web services, database software development, data management resources, and bioinformatics analytical effort and expertise. The aims of the core are: (1) to develop a national-level web-enabled database registry for the secure and confidential collection and integration of clinical and genomic data associated with children suffering from rheumatologic disease; (2) to facilitate comprehensive analyses of gene expression data gathered from all projects in the program and (3) to facilitate the education and training of rheumatology staff in data capture and data analysis using informatics-related software. To accomplish these aims, efforts in the core will be divided between the development of the data system, and the collection and analysis of the data that is brought into the system. To develop a web-accessible database we will use object oriented data modeling approaches for the critical tasks of collecting, processing and using physical samples, and the representation, interpretation and integration of data from all pertinent clinical, laboratory, and genomic studies. A Rheumatology-specific web-portal will provide data entry, access, and analysis capability for appropriate personnel of the integrated clinical and genomic data. Data security and confidentiality will use encrypted web protocols and be consistent with HL7 standards and HIPAA guidelines. Gene expression data will be monitored and screened by core staff for interpretation of its quality, then uploaded and compiled into multi-patient/multi-disease experimental views. Team efforts and synergy of skills are critical for the tasks of complex data analysis, interpretation, and pertinent hypothesis generation. The goals of analyses are to identify critical gene interactions, disease subtypes and therapeutic correlations. Realization of these goals will be supported operationally, analytically and educationally. Discovery of functionally related genes and pathways that distinguish disease subclasses should dramatically improve our understanding of individual patients, biological processes that underlie rheumatologic disease, and lead to optimal therapies.